This is an archived session with Behrooz Kaviani – Senior Solutions Engineer, Arbutus Software – from the Auditopia 2026 Arbutus Conference.
What if the most valuable role for AI in audit analytics isn’t performing the analysis for you, but helping you perform it better?
This session explores AI-assisted analytics rather than AI-generated analytics—using AI to help auditors apply established and proven analytical techniques through natural-language prompts. Through practical examples, we’ll demonstrate how AI can assist with analytical approaches, build and enhance scripts and no-code workflows, and perform ad-hoc analysis.
We’ll also explore how effective prompting and context can improve results, while keeping the underlying analytical logic transparent, explainable and fully traceable—helping auditors embrace AI without introducing a black box between themselves and the evidence.
Learning Objectives
Participants will be able to:
- Understand the distinction between AI-assisted and AI-generated analytics, and how AI can help auditors apply established analytical techniques while keeping the underlying commands and analytical logic visible and fully traceable.
- Apply effective prompting and context-setting techniques to guide an AI assistant in supporting audit analytics, including selecting analytical approaches, performing ad-hoc analysis, and building or enhancing scripts and no-code workflows.
- Recognize the importance of transparency, traceability and data protection in AI-assisted audit analytics, and how these principles allow auditors to understand, review and document how an analysis was performed.
Field of Study: Computer Software & Applications (1 CPE) ~ Program Knowledge: Intermediate ~ Duration: 60 min


Day Sales Outstanding with Python (1 CPE) 
